# Selection of suppliers of repairable equipment with the aim of minimizing costs in the construction and operation phases

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran.

2 Associate Prof., Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran.

Abstract

Objective: Selecting suppliers of industrial systems equipment to minimize the total construction and operation costs and implement it for Feed Water Multi-state System (FWS) of Heat Recovery Steam Generator (HRSG) boilers in Mapna Company.
Methods: Using the Markov chain model results in a mathematical programming model and then analyzing the sensitivity of this model. First, using the Markov chain, different system states are drawn. Then, using the state transfer rate (failure rate and repair rate) of the equipment, the probability of the system being in any of these states is determined parametrically. Then, the Markov chain model results are added to the other constraints of a mathematical model the problem and solved by GAMS software. The effect of cost parameter changes on the optimal solution is calculated individually and then compared in a general graph.
Results: The highest construction and operation costs are in ascending order: 1- the equipment purchasing price, 2- the production capacity reduction cost, 3- the system construction delay penalty, and 4- the system shutdown cost. Also, the relationship between the optimal solution to these parameters is linear in a wide range of changes.
Conclusion: All costs have a direct effect on the design of the Feed Water System (purchase, delay, capacity reduction, and shutdown), but the cost of purchasing equipment has the most significant effect on the total cost. It is therefore recommended to focus entirely on reducing this cost.

Keywords

#### References

Amiri, M., Taghavifard, M.T., Azimi, P., & Aghaei, M. (2019). Multi-Objective Model for determining Optimal Buffer Size and Redundancy-Availability Allocation Simultaneously in Manufacturing Systems. Industrial Management Journal, 11(3), 427-460. (in Persian)
Attar, A., Raissi, S., & Khalili-Damghani, K. (2017). A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems. Reliability Engineering & System Safety, 157, 177-191.
Bisht, S., & Singh, S. B. (2021). Reliability Evaluation of Repairable Parallel-Series Multi-State System Implementing Interval Valued Universal Generating Function. Journal of Reliability and Statistical Studies, 81-120.
Fyffe, D. E., Hines, W. W., & Lee, N. K. (1968). System reliability allocation and a computational algorithm. IEEE Transactions on Reliability, 17(2), 64-69
Ghodsypour, S. H., & O’brien, C. (1997, August). An integrated method using the analytical hierarchy process with goal programming for multiple sourcing with discounted prices. In Proceedings of the international conference on Production Research (ICPR), Osaka, Japan.
Guilani, P. P., Juybari, M. N., Ardakan, M. A., & Kim, H. (2020). Sequence optimization in reliability problems with a mixed strategy and heterogeneous backup scheme. Reliability Engineering & System Safety, 193, 106660.
Houshyar, A. (2005). Reliability and maintainability of machinery and equipment, part 2: benchmarking, life-cyclecost, and predictive maintenance. International Journal of Modelling and Simulation, 25(1), 1-11.
Huang, S. H., & Keskar, H. (2007). Comprehensive and configurable metrics for supplier selection. International journal of production economics, 105(2), 510-523.
Kagnicioglu, C. H. (2006). A fuzzy multiobjective programming approach for supplier selection in a supply chain. The Business Review, 6(1), 107-115.
Kamel, G., Aly, M. F., Mohib, A., & Afefy, I. H. (2020). Optimization of a multilevel integrated preventive maintenance scheduling mathematical model using genetic algorithm. International Journal of Management Science and Engineering Management, 1-11.
Kopfer, H., Kotzab, H., Lasch, R., & Janker, C. G. (2005). Supplier selection and controlling using multivariate analysis. International Journal of Physical Distribution & Logistics Management.
Najafi, A. A., Karimi, H., Chambari, A., & Azimi, F. (2013). Two metaheuristics for solving the reliability redundancy allocation problem to maximize mean time to failure of a series–parallel system. Scientia Iranica, 20(3), 832-838.
Sharifi, M., Cheragh, G., Dashti Maljaii, K., Zaretalab, A., Shahriari, M. (2020). Reliability and Cost Optimization of a System with k-out-of-n Configuration and Choice of Decreasing the Components Failure Rates. Scientia Iranica.
Sharifi, M., Shahriyari, M., Khajepour, A., & Mirtaheri, S. A. (2021). Reliability Optimization of a k-out-of-n Series-Parallel System with Warm Standby Components. Scientia Iranica.
Sobhani, Z., & Shahrokhi, M. (2019). Availability Optimization of a Multi-State Industrial System with the Markov Chain Approach. Industrial Management Journal, 11(3), 380-404. (in Persian)
Teymouri, E., Amiri, M., Olfat, L., & Zandieh, M. (2020). Presenting a Supplier Selection, Order Allocation, and Pricing Model in Multi-item, Single-Period, and Multi-Supplier Supply Chain Management with Surface Response Methodology and Genetic Algorithm Approach. Industrial Management Journal, 12(1), 1-23. (in Persian)
Vanteddu, G., Chinnam, R. B., & Gushikin, O. (2011). Supply chain focus dependent supplier selection problem. International Journal of Production Economics, 129(1), 204-216.